A Dual Perspective on Synthetic Trajectory Generators: Utility Framework and Privacy Vulnerabilities

ArXi:2604.19653v1 Announce Type: new Human mobility data are used in numerous applications, ranging from public health to urban planning. Human mobility is inherently sensitive, as it can contain information such as religious beliefs and political affiliations. Historically, it has been proposed to modify the information using techniques such as aggregation, obfuscation, or noise addition, to adequately protect privacy and eliminate concerns. As these methods come at a great cost in utility, new methods leveraging development in generative models, were.